Noometry

Model comparison

Mistral Large 4 vs Qwen3.5 27B

Mistral Large 4 is the stronger model overall, scoring 43.1 to 41.9 on the Noometry Index.

Last verified . 14 shared benchmarks.

Mistral Large 4 Mistral AI

43.1

Rank #99 Confirmed

Qwen3.5 27B Alibaba (Qwen)

41.9

Rank #127 Confirmed

Summary

  • They share 14 benchmarks with published results for both. Mistral Large 4 scores higher in 6 categories and Qwen3.5 27B in 2 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in coding, where Mistral Large 4 leads 48.6 to 38.9.
  • The biggest single-benchmark swing is NYT Connections (extended): 27.4% for Mistral Large 4 and 47.9% for Qwen3.5 27B.
  • Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $0.68 / $2.09 for Mistral Large 4.
  • Mistral Large 4 accepts more context: 1.05M tokens versus 262K.
  • Qwen3.5 27B has downloadable open weights; the other is API-only.

Side by side

Mistral Large 4Qwen3.5 27B
ProviderMistral AIAlibaba (Qwen)
Noometry Index43.141.9
Released2026-10-062026-02-23
WeightsProprietaryOpen
Context window1.05M262K
Max output262K66K
Input $ / M tokens$0.68$0.30
Output $ / M tokens$2.09$2.40
Results tracked1528

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Category by category

Coding Mistral Large 4 leads

Mistral Large 4: 48.6 (#57), Qwen3.5 27B: 38.9 (#168)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena WebDev15411358
LMArena Coding14751427
WeirdML—39.5%
ALE-Bench—349.45

Agentic & Tool Use Not comparable

Mistral Large 4: —, Qwen3.5 27B: —

BenchmarkMistral Large 4Qwen3.5 27B
Vending-Bench 2—201.98

Reasoning Qwen3.5 27B leads

Mistral Large 4: 22.5 (#192), Qwen3.5 27B: 27.5 (#117)

BenchmarkMistral Large 4Qwen3.5 27B
NYT Connections (extended)27.4%47.9%
LMArena Hard Prompts14441414
Thematic Generalization—45.5%
DTBench—82.4%
LMCA—34%

Math Mistral Large 4 leads

Mistral Large 4: 40.4 (#91), Qwen3.5 27B: 38.8 (#127)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Math14881429
MathArena Final-Answer Competitions—56.7%

Knowledge Qwen3.5 27B leads

Mistral Large 4: 36.6 (#166), Qwen3.5 27B: 38.0 (#150)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Expert14471428
SimpleQA Verified20%—
Vectara Hallucination Rate—12.1%

Multimodal Not comparable

Mistral Large 4: —, Qwen3.5 27B: 39.4 (#59)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Vision—1241

Multilingual Mistral Large 4 leads

Mistral Large 4: 52.6 (#82), Qwen3.5 27B: 50.8 (#115)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Non-English14151390
LMArena Chinese14911478
LMArena Russian14141390
LMArena French—1410
LMArena German—1393
LMArena Japanese—1345
LMArena Korean—1358
LMArena Spanish—1407

Instruction Following Mistral Large 4 leads

Mistral Large 4: 75.0 (#76), Qwen3.5 27B: 73.5 (#119)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Instruction Following14241393

Long Context Too close to call

Mistral Large 4: 43.6 (#89), Qwen3.5 27B: 43.1 (#106)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Longer Query14291413

Writing & Preference Mistral Large 4 leads

Mistral Large 4: 60.4 (#97), Qwen3.5 27B: 59.3 (#111)

BenchmarkMistral Large 4Qwen3.5 27B
LMArena Text14271409
LMArena Creative Writing13611362
LMArena Multi-Turn14241410

Frequently asked questions

Is Mistral Large 4 better than Qwen3.5 27B?

Mistral Large 4 is the stronger model overall, scoring 43.1 to 41.9 on the Noometry Index.

Which is cheaper, Mistral Large 4 or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; Mistral Large 4 lists at $0.68 and $2.09.

Is Mistral Large 4 or Qwen3.5 27B better for coding?

Mistral Large 4 scores higher on coding benchmarks: 48.6 versus 38.9 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 4 does, with 1.05M tokens against 262K.

How many benchmarks do Mistral Large 4 and Qwen3.5 27B share?

14 benchmarks have published results for both models. Mistral Large 4 has 15 scored results on Noometry and Qwen3.5 27B has 28.

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